An optimal parameter estimation method for soft tissue characterization

Yashar Madjidi, Y. Zhong, B. Shirinzadeh, Julian Smith
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引用次数: 1

Abstract

This paper presents a gradient-free direct search estimation method by using genetic algorithm to model and predict the elastic stress response of ligament based on quasi-linear viscoelastic (QLV) theory. An improved genetic algorithm is developed to simultaneously fit the ramping and relaxation experimental data to the QLV constitutive equation for obtaining soft tissue parameters in a time-saving process. Experiments and comparison analysis with the existing methods for two exponential and polynomial QLV models are conducted, demonstrating that the proposed method can accurately estimate soft tissue parameters and satisfy the time-saving requirement of intra-operative soft tissue characterization.
软组织表征的最优参数估计方法
基于准线性粘弹性理论,提出了一种基于遗传算法的无梯度直接搜索估计方法,对韧带弹性应力响应进行建模和预测。提出了一种改进的遗传算法,将爬坡和松弛实验数据同时拟合到QLV本构方程中,从而快速获得软组织参数。对两种指数型和多项式型QLV模型进行了实验并与现有方法进行了对比分析,结果表明,该方法能够准确估计软组织参数,满足术中软组织表征的省时要求。
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